Bank Chatbot

Respond to User Script (Uses LLM)

A very simple Python-based intelligent banking chatbot that uses LangChain and Groq LLM to understand and respond to various banking queries.

Features

• Natural language understanding for banking queries
• Categorizes user requests into 7 distinct categories:
  1. Balance Inquiries
  2. Transactions
  3. Payments
  4. Deposit and Withdrawal Queries
  5. Spending Limits and Budgeting
  6. General Account Information
  7. Assistance and Help
• Template-based response generation
• Secure handling of sensitive banking information
• Interactive command-line interface

Prerequisites

• Python 3.x
• Groq API key

Required Dependencies

langchain-groq
langchain-core
python-dotenv

Installation

1. Clone this repository
2. Install required dependencies using requirements.txt:

   pip install -r requirements.txt

   Alternatively, you can install packages individually:

   pip install langchain-groq langchain-core python-dotenv

3. Create a .env file in the root directory and add your Groq API key:

   GROQ_API_KEY=your_api_key_here
   

Usage

Run the script using:

python respond_to_user.py

The chatbot will start in interactive mode. You can:

• Type your banking queries naturally
• Exit by typing 'quit', 'exit', 'x', or 'q'

Example queries:

You: What's my current balance?
You: Can I transfer money to John?
You: Show me recent transactions

How It Works

1. The chatbot first categorizes user input into one of seven predefined categories using the understand_category() function
2. Based on the category, it selects an appropriate response template
3. The template is processed using the Groq LLM to generate a contextual response
4. Additional follow-up prompts are provided after each response

Project Structure

• respond_to_user.py: Main script containing the chatbot logic
• Templates for different query types:
  • Balance template
  • Payments template
  • Transaction history template
  • Account information template
  • General assistance template

Multilingual Speech Assistant (no LLM)

Overview

A Python-based speech recognition and translation tool that supports multiple Indian languages, enabling voice-based interactions with translation capabilities.

Features

• Speech recognition for multiple languages (Hindi, Tamil, Telugu, Bengali, Malayalam, English)
• Real-time speech-to-text translation
• Text-to-speech functionality
• Language auto-detection
• Cross-platform support (Windows, Linux, macOS)

Prerequisites

• Python 3.7+
• Internet connection for translation and speech services

Installation

1. Install Dependencies

pip install -r requirements.txt

2. Required Packages

• SpeechRecognition
• deep-translator
• gTTS (Google Text-to-Speech)
• pydub
• langdetect

Windows-Specific Setup

For Windows users experiencing PyAudio installation issues:

pip install pipwin
pipwin install pyaudio

Note about pyaudio

• Platform-specific sound modules (automatically handled)
• winsound (for Windows)
• For Linux/macOS sound support, install 'sox' system package

Usage

Run the script:

python speech6.py

Main Menu Options

1. Change native language
2. Start conversation (speech recognition and translation)
3. List App Options in Hindi and Tamil
4. Exit

Dependencies

• Google Translator API
• Google Speech Recognition
• Google Text-to-Speech

Supported Languages

• English
• Hindi
• Tamil
• Telugu
• Bengali
• Malayalam

Important Notes

• Requires active internet connection
• Microphone access needed for speech recognition
• Some features may have limitations based on network and speech recognition accuracy

Troubleshooting

• Ensure all required packages are installed
• Check microphone permissions
• Verify stable internet connection

Please raise an issue if any of the above is not clear or doesn't work.